1. Protecting our Health from Professionals Climate Change: a Training Course for Public Health Chapter 17: Early Warning Systems

2. Impact of Climate Change  Temperature –A 1 o C increase in temperature could lead to an eight percent increase in the incidence of diarrhoea (Checkley et al., 2000)  Humidity  Water ecology (algae,bacteria)  Vector bionomics

3. Background  Improved weather forecasting offers the opportunity to develop early warning systems for weather-based events  Use of early warning systems can save lives (e.g., hurricanes, floods, drought, famine)  There are forecasting models for fascioliasis (liverfluke) based on temperature and precipitation

4. Surveillance vs. Early Warning  Surveillance systems are intended to detect disease outbreaks and measure and summarize data on such outbreaks as they occur  Early warning systems are designed to alert the population and relevant authorities in advance about possible adverse conditions that could lead to a disease outbreak and to implement effective measures to reduce adverse health outcomes

5. Climate forecasts Environmental observations Sentinel cases Early cases Epidemic Response Certainty Time Early WarningSurveillance Early Warning vs. Surveillance

6. Lessons Learned from Famine Early Warning Systems  Climate is only one of many determinants that could be included in an early warning system  Early warning of a crisis is no guarantee of prevention

7. Lessons Learned from Famine Early Warning Systems (cont.)  Interest in preventing a crisis is part of a wider political, economic, and social agenda. In many cases governments are not directly accountable to vulnerable populations  In most cases, the purpose of early warning is undermined as relief arrives too late due to poor organization at the donor and/or national level

8. Early Warning Systems  The system should be developed with all relevant stakeholders to ensure that the issues of greatest concern are identified and addressed  A basic requirement is that the community or region has sufficient public health and social infrastructure to undertake its design and implementation

9. Early Warning Systems (cont.)  The principal components of an early warning system include –Identification and forecasting of weather conditions –Prediction of possible health outcomes –An effective and timely response plan –Ongoing evaluation of the system and its components –Sentinel sites, i.e. monitor seroconversion in pigs to forecast possible Japanese encephalitis outbreak in human population

10. Effective Early Warning Systems  Provide warning in sufficient time for action  Are affordable –Require minimal skill and training to operate and maintain  Give minimal false positive or negative responses  Are robust, reproducible, and verifiable  Can be easily modified to address a changing climate

11. Components of an Early Warning System for Infectious Diseases

12. Identification and Forecasting  Multiple disciplines are required to develop accurate, effective, and efficient population- and location-specific early warning systems  Biometeorology contributes to the development of models that incorporate associations between weather and health outcomes to predict possible health burdens associated with changing weather patterns

13. Development and Utilization of Climate Information  Data –Spatial and temporal coverage of critical weather variables  Methods –Simple correlation; trend analysis; etc.  Acceptability / credibility –Timely; relevant; compatible with existing decision-making protocols; accessible  Context –Early warning systems are not contingent on climate information alone

14. El Niño

16. Geographical Spread of Dengue Fever in SEA Region Countries in SEA Region reporting Dengue in 2003 and in 2007

17. Prediction of Possible Health Outcomes  Evaluate potential for epidemic transmission  Identify epidemic-prone areas and populations at risk to allow rapid –Prediction and detection –Targeting of response –Planning of logistics for response  Quantify climatic and non-climatic disease risk factors  Quantify the link between climate variability and disease outbreaks –Construct predictive models

18. Average Percentage Deviation in Malaria Cases, Colombia Niño +1 Niño 0 Other Years (1960-1992) 25 15 5 0 -5 -15 -25 Deviation From Trend in Malaria Cases (%) Bouma et al., 1997

19. Using Local Weather Data to Predict Epidemics Incidence of malaria in highland site in Ethiopia (black line). Incidence predicted from a model using local meteorological data (blue dotted line). Teklehaimanot et al., 2004

20. Weather-Based Prediction of Plasmodium falciparum Malaria in Ethiopia: Comparison with Early Detection Teklehaimanot et al., 2004

21. Components of a Response Plan  Where the response plan will be implemented  When interventions will be implemented, including thresholds for action  What interventions will be implemented  How the response plan will be implemented  To whom the interventions will be communicated Ebi and Schmier, 2005

22. Survey Results on Whether Older Adults Knew that a Heatwave Early Warning Had Been Called No Yes Surveys were conducted in Dayton, Philadelphia, and Phoenix, in the US and in Toronto, Canada Sheridan, 2007

23. Heatwave Survey Conclusions 90% Knew a heatwave early warning had been called. 75% Knew of at least one action to take to reduce their vulnerability to the heat 45% Actually took one or more actions Sheridan, 2007

24. Monitoring and Evaluation  Need to establish programs to answer these questions (at a minimum) –What are the chances that the system will fail to predict an epidemic, and how many lives could be lost? –What are the chances of sounding a false alarm, thereby wasting resources and undermining public trust? –Is the system as responsive as needed? How many lives could have been saved if the system response was faster? –Is the system cost-effective?

25. Candidate Diseases for Epidemic Early Warning Systems  Cholera  Malaria  Dengue fever  Japanese encephalitis  Influenza  Leptospirosis  Rift valley fever (Major zoonosis)  Borreliosis (Tick-borne)  Others

26. What Have We Learned from Other Systems?  Early warning systems can save lives (e.g., hurricanes, famine)  Climate is only one of many determinants that can help in early warning systems  Early warning of a crisis is no guarantee of prevention  Capacity and willingness to respond is essential